摘要
通过大数据分析技术可有效解决传统项目管理方法在衡量任务工作量和工期偏差中的主观性和局限性,基于历史项目任务数据对随机森林分类器进行训练,使分类器输出结果符合实际项目应用,并通过实证分析较好地实现了项目成本和进度偏差识别。
In the project management process,big data analysis technology can effectively avoid subjectivity and limitations of traditional project management methods in measuring the deviation of task workload and duration.Based on historical project task data,the random forest classifier is adopted to make the output result of the classifier conform to the actual project application.Through empirical analysis,better realization of project cost and schedule deviation identification is achieved.
作者
刘保鹏
丁尤蓉
LIU Baopeng;DING Yourong(Logistics Management Office,Wuxi Institute of Technology,Wuxi 214121,China)
出处
《无锡职业技术学院学报》
2021年第6期42-46,共5页
Journal of Wuxi Institute of Technology
关键词
项目管理
挣值管理
大数据
随机森林
project management
earned value management
big data
random forest